"Statistical Learning Methods"-Summary of Reading Notes (Summary 15/27)

The article is mainly used to record the study notes of the "Statistical Learning Methods (Second Edition)" of Teacher Li Hang. It is mainly based on the content of the textbook. The preliminary plan is to slowly organize the knowledge points according to the chapter list. I hope to learn from each other and improve together!

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table of Contents

Part 1 Supervised Learning

Statistical learning method reading notes (1)-an overview of statistical learning and supervised learning

Statistical learning method reading notes (2)-Perceptron

Statistical learning method reading notes (3)-k nearest neighbor method

Statistical Learning Methods Reading Notes (4)-Naive Bayes Method

Statistical learning method reading notes (5)-decision tree

Statistical Learning Methods Reading Notes (6)-Logistic Regression and Maximum Entropy Model

Statistical learning method reading notes (7)-Support Vector Machine

Statistical learning method reading notes (eight)-promotion method

Statistical learning method reading notes (9)-EM algorithm and its promotion

Statistical learning methods reading notes (10)-hidden Markov model

Statistical Learning Methods Reading Notes (11)-Conditional Random Field

Statistical learning method reading notes (12)-a summary of supervised learning methods

Chapter 2 Unsupervised Learning

Statistical Learning Methods Reading Notes (13)-Overview of Unsupervised Learning

Statistical learning method reading notes (14)-clustering method

Statistical learning method reading notes (15)-singular value decomposition (to be updated)

Statistical learning method reading notes (16)-principal component analysis (to be updated)

Reading Notes of Statistical Learning Methods (17)-Latent Semantic Analysis (to be updated)

Statistical Learning Methods Reading Notes (18)-Probabilistic Latent Semantic Analysis (to be updated)

Statistical learning method reading notes (19)-Markov chain Monte Carlo method (to be updated)

Reading Notes for Statistical Learning Methods (20)-Potential Dirichlet Distribution (to be updated)

Statistical learning method reading notes (21)-PageRank algorithm (to be updated)

Statistical learning methods reading notes (22)-Summary of unsupervised learning methods (to be updated)

appendix

Statistical learning method reading notes (23)-Appendix A Gradient Descent Method

Reading Notes of Statistical Learning Methods (24)-Appendix B Newton's Method and Quasi-Newton's Method (to be updated)

Reading Notes on Statistical Learning Methods (25)-Appendix C Lagrangian Duality (to be updated)

Statistical Learning Method Reading Notes (26)-Appendix D Basic Subspace of Matrix (to be updated)

Statistical Learning Methods Reading Notes (27)-Appendix E The definition of KL divergence and the properties of Dirichlet distribution (to be updated)